A few weeks ago, I took an initial (and someone rudimentary) dive into tying Statcast data to Ottoneu. Specifically, looking at the Fangraphs Points (FGpts) format. Like in real baseball, when the ball leaves the bat with a higher exit velocity, it is more likely to produce more favorable results. This was to be expected. The way the scoring settings for FGpts was developed was through linear weights, so it would make sense that the distribution of points per batted ball ties closely to reality. Today, I am going to look at the batted balls hit though the all star break (actually, just before the break as I pulled this July 6th) and examine the expected points per ball in play on specific batted ball types. Let’s get started.

Read the rest of this entry »

First things first, you can check out all of my 10 Bold Predictions here, though, I’ll be providing them with a review of how they are fairing below. Predictably, some have a chance — a good chance, even — to hit. Others, however, are toast already. Let’s jump into the predictions. Read the rest of this entry »

Episode 279 – You Might Be Boring But You Wouldn’t Be Crazy

The latest episode of “Field of Streams” is live!

In this episode, Dylan Higgins and Matthew Dewoskin discuss the All-Star break, the big trade between the White Sox and the Cubs, Whit Merrifield being legit, finally almost believing in Jhoulys Chacin enough to take at home, a trio of strong pick options on Sunday, Dylan going out on a limb with a Nick Williams fantasy comp, the return of Marcus Semien, the return of Kolten Wong, and the worst sports radio call ever.

Read the rest of this entry »

Podcast (field-of-streams): Play in new window | Download

Subscribe: RSS

Chat transcript is below!

Read the rest of this entry »

Before I get into just how completely wrong my first prediction is/was, I want to briefly explain my outlook for the Bold Predictions in the first place.  I think these should be fun and spark conversation. As a result, they should probably be controversial, at least in part. There should be a reason for each pick, and the reason shouldn’t necessarily be built on a strong hypothesis. If you have a solid reason to believe something then you aren’t talking about a bold prediction, it is just a normal prediction. Bold predictions should be built on a questionable foundation, that’s the fun part.

I view this as a testing ground for ideas. Most of these are arguments I would have otherwise quietly kept to myself. Any by quietly I mean tweeted out once and then retweeted at the end of the season if they came true. Just kidding.

Having said all that, let’s get to my first and worst prediction. Oh jeez, here we go. Read the rest of this entry »

I’ve never performed a mid-season review of my pre-season bold predictions because I typically forget what I predicted and like to be surprised when I recap them six months later. But the article I wanted to write cannot be done, so here I am stepping into uncharted waters. Can you feel the excitement?! My goal this year is to beat my personal record setting 2016 performance of four correct bold predictions. Let’s see if I have any chance whatsoever.

Read the rest of this entry »

At the midway point of the season, it’s always interesting to see how teams are utilizing their pitching staffs. I’ve been examining workloads through the metric I created, called Fatigue Units. This metric accounts for days between appearances, stress during pitching, and time between pitches – you can read more about it here. TLDR; Fatigue Units appear to be a more accurate indicator of “overworked” pitchers than pitches, or innings pitched.

To start off – what does the midway point indicate about a pitcher’s workload? It doesn’t necessarily indicate what the workload will be by season’s end, but it does say that the pitcher has worked hard in the first half. It definitely says that the team has trusted that pitcher, and, that pitcher is very good. Here’s what the halfway point workloads looked like in 2016.

Read the rest of this entry »

Since 2013, I have polled you dashingly attractive readers on which group of pitchers you think will post the better aggregate ERA post all-star break. The two groups were determined based on ERA-SIERA disparity, pitting the underperformers versus the overperformers during the pre-all-star break period.

Read the rest of this entry »

Yesterday, I identified a group of hitters worth buying for their home run upside, given the discrepancy between their actual HR/FB rate and xHR/FB rate. Today, I move over to batting average, as I identify the hitters whose xBABIP marks most exceed their actual BABIP marks. These are the guys to target for batting average that you may be able to get at a discount.

Read the rest of this entry »

Today at the Prospect Stock Watch we take a look at three of the lesser-known prospects to appear yesterday in the MLB Futures Game in Miami.

Jaime Barria, RHP, Angels: It’s becoming easier and easier to find intriguing prospects in the Angels system to write about — after years of mediocrity. This 20-year-old Panamanian pitcher isn’t the most physical but he commands three pitches that should grade out as average or better. He’s struck out 83 batters so far this season with just 16 walks in 95.2 innings of work. His sturdy frame could allow him to develop into an innings-eating, back-of-the-rotation arm with the ceiling of a No. 3 starter.

After beginning the year in high-A ball, Barria has now made five starts in double-A and, if he continues to succeed at the level, he could open 2018 in triple-A with an eye towards a mid-2018 big league debut. The system doesn’t have many near-MLB-ready impact arms and the big league rotation is fragile (both due to health issues and impending free agencies) so players like Barria could be key to the organization’s successes in the near future.

Read the rest of this entry »